Obstacle Position and Extent Measurement By Automotive Radar

ABSTRACT

Aspects of the disclosure are directed towards obstacle position and extent measurement. In accordance with one aspect, obstacle detection includes creating one or more interferometric measurements to generate a flow of response position locations using a flow of range/Doppler detections by fitting a parametric expression; and deriving one or more scatterer positions and obstacle position and extent measurements from the flow of response position locations.

CLAIM OF PRIORITY UNDER 35 U.S.C. § 119

The present Application for Patent claims priority to ProvisionalApplication No. 62/593,255 entitled “OBSTACLE POSITION AND EXTENTMEASUREMENT BY AUTOMOTIVE RADAR” filed Dec. 1, 2017, and assigned to theassignee hereof and hereby expressly incorporated by reference herein.

TECHNICAL FIELD

This disclosure relates generally to the field of radar detection, and,in particular, to obstacle position and extent measurement by anautomotive radar.

BACKGROUND

The present disclosure relates to an automotive radar for measuring thepositions and extents of obstacles on a road. In one example, a purposefor the measurements is to determine whether a vehicle on the road mustchange course to avoid colliding with an obstacle. In one example, themeasurements may include an obstacle's height.

SUMMARY

The following presents a simplified summary of one or more aspects ofthe present disclosure, in order to provide a basic understanding ofsuch aspects. This summary is not an extensive overview of allcontemplated features of the disclosure, and is intended neither toidentify key or critical elements of all aspects of the disclosure norto delineate the scope of any or all aspects of the disclosure. Its solepurpose is to present some concepts of one or more aspects of thedisclosure in a simplified form as a prelude to the more detaileddescription that is presented later.

In one aspect, the disclosure provides techniques and apparatus relatingto obstacle position and extent measurement. Accordingly, the disclosureprovides a method for obstacle detection, the method including creatingone or more interferometric measurements to generate a flow of responseposition locations using a flow of range/Doppler detections by fitting aparametric expression; and deriving one or more scatterer positions andobstacle position and extent measurements from the flow of responseposition locations.

In one example, the method further includes receiving a receive radarwaveform and generating a digitized radar data from the receive radarwaveform. In one example, the receive radar waveform is a scaled replicaof a transmit radar waveform with a time delay τ (tau) and a Dopplershift ν (nu) for a scatterer. In one example, the receive radar waveformis a scaled replica of a transmit radar waveform.

In one example, the method further includes forming a flow ofrange/cross-range radar images from the digitized radar data. In oneexample, the flow of range/cross-range radar images includes a pluralityof resolution cells. In one example, the plurality of resolution cellsincludes a range resolution determined by a signal bandwidth and across-range resolution determined by an angular rotation of radar lineof sight.

In one example, the method further includes generating the flow ofrange/Doppler detections from the flow of range/cross-range radarimages. In one example, the method further includes generating thetransmit radar waveform, wherein the transmit radar waveform is acoherent pulsed radar waveform with a plurality of pulses over acoherent time duration. In one example, the parametric expressionincludes a relative spacing of a ground-bounce and a direct return froma scatterer.

In one example, the method further includes deriving the one or morescatterer positions and obstacle position and extent measurements bydetermining a simultaneous solution for a plurality of scatterers with aleast-squares fit using numerical optimization. In one example, themethod further includes deriving the one or more scatterer positions andobstacle position and extent measurements by determining an iterativescatterer-by-scatterer solution based on a deconvolution algorithm. Inon example, the deconvolution algorithm is a CLEAN algorithm.

Another aspect of the disclosure provides an apparatus for obstacledetection, the apparatus including an interferometric processor tocreate one or more interferometric measurements to generate a flow ofresponse position locations using a flow of range/Doppler detections byfitting a parametric expression; and a scatterer processor, coupled tothe interferometric processor, to derive one or more scatterer positionsand obstacle position and extent measurements from the flow of responseposition locations. In one example, the interferometric processor andthe scatterer processor are two separate components of the apparatus.

In one example, the apparatus further includes a radar transceiver toreceive a receive radar waveform and to generate a digitized radar datafrom the receive radar waveform. In one example, the receive radarwaveform is a scaled replica of a transmit radar waveform with a timedelay τ (tau) and a Doppler shift ν (nu) for a scatterer. In oneexample, the transmit radar waveform is a coherent pulsed radar waveformwith a plurality of pulses over a coherent time duration.

In one example, the apparatus further includes an image processor,coupled to the radar transceiver, to form a flow of range/cross-rangeradar images from the digitized radar data. In one example, theapparatus further includes a detection processor, coupled to the imageprocessor, to generate the flow of range/Doppler detections from theflow of range/cross-range radar images.

In one example, the scatterer processor derives the one or morescatterer positions and obstacle position and extent measurements bydetermining a simultaneous solution for a plurality of scatterers with aleast-squares fit using numerical optimization. In one example, thescatterer processor derives the one or more scatterer positions andobstacle position and extent measurements by determining an iterativescatterer-by-scatterer solution based on a deconvolution algorithm.

These and other aspects of the disclosure will become more fullyunderstood upon a review of the detailed description, which follows.Other aspects, features, and implementations of the present disclosurewill become apparent to those of ordinary skill in the art, uponreviewing the following description of specific, exemplaryimplementations of the present invention in conjunction with theaccompanying figures. While features of the present invention may bediscussed relative to certain implementations and figures below, allimplementations of the present invention can include one or more of theadvantageous features discussed herein. In other words, while one ormore implementations may be discussed as having certain advantageousfeatures, one or more of such features may also be used in accordancewith the various implementations of the invention discussed herein. Insimilar fashion, while exemplary implementations may be discussed belowas device, system, or method implementations it should be understoodthat such exemplary implementations can be implemented in variousdevices, systems, and methods.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example arrangement of range/cross-rangeresolution cells on the ground when a vehicle turns.

FIG. 2 illustrates an example arrangement of cross-range resolutioncells in a single range bin when a vehicle moves straight, toward an ‘x’at a depicted center point.

FIG. 3 illustrates an example of relative positions of a direct responsefrom a scatterer.

FIG. 4 illustrates an example block diagram of an automotive radar inaccordance with the present disclosure.

FIG. 5 illustrates an example block diagram of an automotive radarseparated into transmit antenna elements, receive antenna elements, anautomotive radar transceiver with digitized data flowing from the radartransceiver, and a radar microcontroller.

FIG. 6 illustrates an example flow diagram for measuring positions andextents of obstacles on a road.

DETAILED DESCRIPTION

The detailed description set forth below in connection with the appendeddrawings is intended as a description of various configurations and isnot intended to represent the only configurations in which the conceptsdescribed herein may be practiced. The detailed description includesspecific details for the purpose of providing a thorough understandingof various concepts. However, it will be apparent to those skilled inthe art that these concepts may be practiced without these specificdetails. In some instances, well known structures and components areshown in block diagram form in order to avoid obscuring such concepts.

In one example, a radar may produce a two-dimensional output in eachchannel, e.g., a radar image as a function of two dimensions, such asrange and cross-range (or Doppler offset). A channel may be associatedwith one transmit antenna and one receive antenna. For example, theradar image may be comprised of a plurality of two-dimensionalresolution cells, where a first dimension is comprised of a plurality ofrange bins (e.g., range resolution cells) and a second dimension iscomprised of a plurality of cross-range bins (or Doppler bins) (e.g.,cross-range resolution cells or Doppler resolution cells). Eachresolution cell may include one or more scatterers, i.e., an objectwhich reflects transmitted electromagnetic waves from a radartransmitter and converts it into received electromagnetic waves to aradar receiver. One example of an object is an obstacle, for example, anobstacle in a road. In one example, the automotive radar may be used todetect obstacles in the road so that the vehicle may avoid a collisionwith the obstacle.

In one example, a radar may possess multiple channels for spatialdiversity (e.g., electronically scanned array automotive radars,Multiple Input Multiple Output (MIMO) automotive radars). For example,transmit and receive antennas in the radar may be positioned in closeproximity. For example, the spacings of the antennas (i.e., bothtransmit antennas and receive antennas) may determine transmit andreceive beamwidths, i.e., transmit and receive angular resolution. Thebeamwidths may be much larger than obstacles at the ranges of interest.That is, the angular resolution of the radar typically may not resolve,i.e., subdivide, a radar image of an obstacle into a plurality ofresolution cells. In one example, the transmit antenna produces atransmit antenna pattern, and the receive antenna produces a receiveantenna pattern. The transmit antenna pattern and the receive antennapattern may each include a mainlobe (i.e., a primary lobe aroundboresight in the transmit or receive antenna) and a plurality ofsidelobes (i.e., secondary lobes away from boresight in the transmit orreceive antenna pattern). The present disclosure applies whether or notthe angular resolution of the radar subdivides the radar image of theobstacle into resolution cells, and applies for both fixed and scannedbeams. For example, the obstacle may include a plurality of scattererswithin the plurality of resolution cells.

In one example, for an accurate measurement of positions of theplurality of scatterers constituting an obstacle, thereby defining itsextent, the radar must subdivide the radar image into resolution cells.In one example, a radar signal bandwidth provides range resolution(i.e., size of the range resolution cell). In one example, angularrotation of a radar line of sight with respect to the obstacle providescross-range resolution (i.e., size of the cross-range resolution cell).In one example, a plurality of range resolution cells and cross-rangeresolution cells comprises a range/cross-range radar image. In oneexample, shapes of the cross-range resolution cells may depend onwhether the vehicle turns and, if it turns, the size of the cross-rangeresolution cell is inversely proportional to the size of the vehicleturn. The present disclosure applies whether or not the vehicle turns.

In one example, the present disclosure deduces physical positions ofscatterers by combining measured range/cross-range positions ofresponses in a radar image, interferometric measurements of angularpositions of those responses, and/or contextual information (e.g., thepropagation path for some responses includes reflection from theground). In one example, the interferometric measurements accommodatemultiple responses within a resolution cell, for example, from one ormultiple scatterers, from ground-bounce and/or direct returns, and/orfrom mainlobe and sidelobe responses of the receive antenna.

FIG. 4 illustrates an example block diagram 400 of an automotive radarin accordance with the present disclosure. FIG. 4 shows one or moretransmit antenna elements 401. Although only one transmit antennaelement is shown, one skilled in the art would understand that more thanone transmit antenna element may be included within the spirit and scopeof the present disclosure. FIG. 4 also shows four receive antennaelements 402. Although four receive antenna elements are shown, oneskilled in the art would understand that less than four or more thanfour antenna elements may be included within the spirit and scope of thepresent disclosure.

A radar transceiver 410 is shown coupled to the transmit antenna element401 and the receive antenna elements 402. In one example the radartransceiver 410 includes a radar transmitter. And, in one example, theradar transceiver 410 includes a radar receiver. In one example, theradar transceiver 410 may generate a transmit radar waveform which isconverted to a transmitted electromagnetic wave 414 by the one or moretransmit antenna elements 401. The transmit radar waveform may, forexample, be a coherent pulsed radar waveform with a plurality of pulsesover a coherent time duration.

In one example, the radar transceiver 410 may receive a receive radarwaveform from a received electromagnetic wave 416. The receive radarwaveform may be a scaled replica of the transmit radar waveform. In oneexample, the receive radar waveform may a scaled replica of the transmitradar waveform with a time delay τ (tau) and a Doppler shift ν (nu) fora scatterer. In one example, output from the radar transceiver 410 isdigitized radar data 420 for each receive antenna element 402. In oneexample, the digitized radar data 420 is generated by ananalog-to-digital converter (ADC) (not shown) which converts the receiveradar waveform to the digitized radar data 420 in the radar transceiver410. In one example, the digitized radar data 420 may be indexed (i.e.,labeled) as a function of delay index and a pulse index. In one example,the delay index may be denoted as a fast time. In one example, the pulseindex may be denoted as a slow time.

In one example, the digitized radar data 420 may include amplitudeinformation and phase information of the receive radar waveform. Thatis, the digitized radar data 420 may be expressed as a sequence ofcomplex values. In one example, the amplitude information represents amagnitude of the receive radar waveform. In one example, the phaseinformation represents a relative phase of the receive radar waveform.In one example, the digitized radar data 420 may be expressed in anorthogonal signal format, for example, with in-phase components andquadrature components.

In one example, an image processor 430 accepts the digitized radar data420 as an input and forms a flow of range/cross-range radar images. Inone example, the image processor 430 outputs the flow ofrange/cross-range radar images 431. The flow of range/cross-range radarimages 431 may include a plurality of radar images from each channel. Inone example, the flow of range/cross-range radar images 431 includes aplurality of range and cross-range resolution cells.

In one example, the plurality of resolution cells may be indexed by arange index and a cross-range index. Angular rotation of the radar lineof sight over the coherent time duration may determine a size of thecross-range resolution cells.

The flow of range/cross-range radar images 431 may include a designationof image type. For example, image type may include focused image,unfocused image, partially focused image, turning-radar image, andnon-turning-radar image. In one example, a non-turning radar image maybe a forward-looking SAR image.

In one example, the flow of range/cross-range radar images 431 may beexpressed as a sequence of complex image values. For example, thesequence of complex image values may include amplitude image values andphase image values. And, the sequence of complex image values mayinclude in-phase image values and quadrature image values.

In one example, a detection preprocessor 440 (e.g., a processor coupledto a memory unit) inputs the flow of range/cross-range radar images 431which is used for thresholding, Constant False Alarm Rate (CFAR)detection, or similar detection operation. In one example, the detectionpreprocessor 440 generates a flow of range/Doppler detections 441 asoutputs. In one example, the flow of range/Doppler detections 441 is aflow of range/cross-range detections.

In one example, the flow of range/Doppler detections 441 may beexpressed as a sequence of complex detection values. For example, thesequence of complex detection values may include amplitude detectionvalues and phase detection values. And, the sequence of complexdetection values may include in-phase detection values and quadraturedetection values.

In one example, the flow of range/Doppler detections 441 is sent asinput to an interferometric processor 450. In one example, theinterferometric processor 450 may be coupled to a memory unit. In oneexample, the interferometric processor 450 generates interferometricmeasurements. For example, the interferometric measurements may beproduced by coherent combination of the flow of range/Doppler detections441 to generate a flow of response position locations 452. In oneexample, coherently combining of the flow of range/Doppler detections441 includes processing a sequence of complex detection values. In oneexample, the flow of response position locations 452 is sent as an inputto a scatterer processor 460. In one example, the scatterer processor460 generates scatterer positions 461 and obstacle positions and extentmeasurements 462.

As shown in FIG. 4, one or more transmit antenna elements 401 andmultiple receive antenna elements 402 may be connected to the automotiveradar transceiver 410. Digitized radar data 420 from each receivechannel may be processed in image processor 430 into a flow ofrange/cross-range radar images 431 for each real receive channel orvirtual receive channel. In one example, several seconds of data may beprocessed coherently (i.e., a coherent dwell) to form the image. In oneexample, coherent processing involves digital signal processing withamplitude information and phase information of the digitized radar data420. In one example, the coherent dwell may be reduced relative to amaximum coherent dwell time, depending on vehicle speed, position of theradar on the vehicle, and/or whether an autonomous driving system is inuse (in which case, small vehicle maneuvers within a lane can beexploited). In the case of a MIMO radar, the image processor 430includes the MIMO processing required to generate virtual receivechannels.

In one example, the flow of range/cross-range radar images 431 includesan image for each channel. The images may be inputted to a detectionpreprocessor 440 which outputs a flow of detections, for example, theflow of range/Doppler detections 441. Each flow of detections mayinclude complex image values (e.g., amplitude image values and phaseimage values) from corresponding pixels of an image for each channelthat is inputted to the detection preprocessor 440. The flow ofrange/Doppler detections 441 may be inputted to interferometricprocessor 450. Interferometric measurements and a flow of responseposition locations may be fused into scatterer positions 461, which maybe clustered into obstacle position and extent measurements 462 inscatterer processor 460.

In one example, when a vehicle turns, the flow of range/cross-rangeradar images 431 may be formed in the image processor 430 via digitalsignal processing. In one example, the digital signal processingincludes a motion compensation of a single point followed by atwo-dimensional fast Fourier transform (FFT). Motion compensation may beperformed, for example, by autofocusing. Motion compensation may includequadratic phase error processing based on sensed vehicle dynamicparameters. In one example, sensed vehicle dynamic parameters mayinclude position, velocity and acceleration as functions of time.

In one example, a plurality of resolution cells in a radar image isgenerated which defines a horizontal grid of nearly rectangularresolution cells. FIG. 1 illustrates an example arrangement 100 ofrange/cross-range resolution cells on the ground when a vehicle turns.

Synthetic-aperture radar (SAR) is a form of radar that is used to createtwo-dimensional images.

In one example, when a vehicle trajectory is a straight line, imageformation processing in the image processor 430 may be forward-lookingSAR (FSAR) image formation processing. For example, annular cross-rangeresolution cells may be generated, centered on the line of the vehicletrajectory and with width decreasing with the distance from the vehicletrajectory, as shown in FIG. 2. FIG. 2 illustrates an examplearrangement 200 of cross-range resolution cells in a single range binwhen a vehicle moves straight, toward an ‘x’ at a depicted center point210.

For example, a radar may combine the plurality of receive channels in avariety of ways. In one example, a sum channel may be a superposition oftwo or more receive channels. In one example, a difference channel maybe a subtraction between two or more receive channels.

In one example, an application of digital signal processing may beprescribed as an input, determined from auxiliary data if available, ordetermined adaptively from radar data. In the latter case, an image maybe formed in a sum channel as if the vehicle is turning and the degreeof focus of the image is measured. For example, the degree of focus maybe measured by an absolute value of its entropy. In one example, entropymay be defined as H=Σp_(i) log p_(i), where p_(i) is a probabilitymeasure, log is a logarithmic function (with base b) and Σ representssummation over index i.

If the measured degree of focus is below a predetermined threshold, theforward-looking SAR (FSAR) image may be generated in a sum channel andthe degree of focus is measured. In one example, the flow ofrange/cross-range radar images 431 may be a better-focused image type,with a same image type for each channel.

The flow of range/cross-range radar images 431 from each receive channelmay be inputted to detection preprocessor 440, which may employintensity thresholding or Constant False Alarm Rate (CFAR) processing.The flow of range/Doppler detections 441 may be input to interferometricprocessor 450, which applies processing in accordance with the type ofimage formed. For both types of image, the interferometric processor 450may derive scatterer positions in each resolution cell containingrange/Doppler detections 441 by fitting a parametric expression to themulti-channel complex-data of the response. The parametric expressionsmay incorporate relative spacing of ground-bounce and direct returnsfrom each scatterer, depending on the image type and the size of theresolution cell. In one example, ground-bounce is a radar return from apropagation path that reflects from the ground.

FIG. 3 illustrates an example 300 of relative positions of a directresponse and ground-bounce responses from a scatterer. In the example ofFIG. 3, no ground-bounce is indicated by 0. In the example of FIG. 3, asingle ground-bounce response is indicated by 1 and the bouncing may beon either the transmit path or the receive path. In the example, of FIG.3, a double ground-bounce response is indicated by 2. Stated anotherway, 0 indicates the location of the direct response, 1 indicates thelocation of a single ground-bounce response and 2 indicates the locationof a double ground-bounce response.

The right image of FIG. 3 shows the relative positions of the directresponse from a scatterer (indicated by a 0), the two singleground-bounce responses from the scatterer (indicated by a 1), and thedouble ground-bounce response from the scatterer (indicated by a 2) inan image formed via forward-looking SAR (FSAR) processing. Although theextents of the resolution cells depend on the vehicle motion and theposition of the radar, the single ground-bounce responses may appear atground level and the double ground-bounce response appears as a mirrorresponse of the direct response.

Also, of the responses from a single scatterer, the double-bounceresponse may fall in the narrowest cross-range resolution cell and thedirect response may fall in the widest cross-range resolution cell. Inone example, interferometric measurements on each response maycorrespond to the last point of reflection for that response. If the setof responses from a scatterer at a clearance height of the vehicle'sundercarriage are resolved from each other, the interferometricprocessing may treat each resolution cell as including some number (tobe determined) of uncorrelated responses. If not, the interferometricprocessing may treat each resolution cell as including a number ofquartets (i.e., sets of four) of correlated responses, with each quartetof correlated responses including the direct return and theground-bounce returns from a single scatterer.

In one example, a right-handed coordinate system may be used to definevehicle motion along a vehicle trajectory, where x is perpendicular tothe vehicle trajectory, y is along the vehicle trajectory and z isvertical, with a cross-range coordinate ρ=√{square root over (x²+z²)}.In one example, uncorrelated responses I_(j) in a resolution cell arerepresented for receive channel j as

$I_{j} = {\sum\limits_{k}^{\;}{{P( {y_{k},\rho_{k}} )}a_{k}{\exp \lbrack {i( {{4\pi \; {y_{k}/\lambda}} + {\alpha_{j}x_{k}} + {\epsilon_{j}z_{k}}} )} \rbrack}}}$

where α_(j) and ∈_(j) are coefficients determined by a receive antennalayout, P(y,ρ) is a real-valued point target response of the image, λ isa wavelength of a received electromagnetic wave and the sum is overresponses in the resolution cell. In one example, there are fourparameters (a_(k), x_(k), y_(k), z_(k)) to be determined per responseI_(j) and one complex number per receive channel, so with N receivechannels, the interferometric processor may determine parameters of upto N/2 responses per resolution cell.

For some of the examples described herein, the responses may be fromscatterers located within the resolution cell using mainlobes of thereceive antenna. Or, the responses may be from scatterers locatedoutside the resolution cell using sidelobes of the receive antenna. Inone example, the parameters may be derived by a simultaneous solutionfor multiple scatterers via a least-squares fit using numericaloptimization, or via an iterative scatterer-by-scatterer solution basedon a deconvolution algorithm, for example, a CLEAN algorithm. In oneexample, the CLEAN algorithm: finds the strongest pixel across allchannels (at each iteration). In one example, the CLEAN algorithmmeasures the interpolated range/cross-range peak position in the channeland uses all channels to derive the parameters for a response or a setof correlated responses. In one example, the CLEAN algorithm subtracts aderived response from all channels.

For forward-looking SAR (FSAR) processing, the quartets of correlatedresponses in a resolution cell may be represented for receive channel jas

$I_{j} = {\sum\limits_{k}^{\;}{{{P( {y_{k},\rho_{k}} )}\lbrack {{a_{k}{\exp ( {i\; \epsilon_{j}z_{k}} )}} + {b_{k}{\cos ( {\epsilon_{j}z_{k}} )}} + {c_{k}{\exp ( {{- i}\; \epsilon_{j}z_{k}} )}}} \rbrack}{\exp \lbrack {i( {{4\pi \; {y_{k}/\lambda}} + {\alpha_{j}x_{k}}} )} \rbrack}}}$

There are six parameters (a_(k), b_(k), c_(k), x_(k), y_(k), z_(k)) tobe determined per quartet, so the interferometric processor maydetermine parameters of up to N/3 quartets per resolution cell.

The left image of FIG. 3 shows an example of relative positions of adirect response from a scatterer (indicated by a 0), two singleground-bounce responses from the scatterer (indicated by a 1), and adouble ground-bounce response from the scatterer (indicated by a 2) inan image formed via conventional processing. In one example, rangeseparation of the responses is a product of scatterer height and sine ofa grazing angle, so the responses may rarely be resolved. Accordingly,the processing may process quartets of responses. The quartets ofcorrelated responses in a resolution cell may be represented for receivechannel j as

$I_{j} = {\sum\limits_{k}^{\;}{{\exp \lbrack {i( {{\alpha_{j}x_{k}} + {4\pi \; {y_{k}/\lambda}}} )} \rbrack}\{ {{a_{k}{P( {x_{k},y_{k}} )}{\exp ( {i\; \epsilon_{j}z_{k}} )}} + {b_{k}{P( {x_{k},{y_{k} + {z_{k}\sin \; \delta}}} )}{\exp \lbrack {i\; 4\; \pi \; z_{k}\sin \; {\delta/\lambda}} \rbrack}{\cos ( {\epsilon_{j}z_{k}} )}} + {c_{k}{P( {x_{k},{y_{k} + {2z_{k}\sin \; \delta}}} )}{\exp \lbrack {i( {{8\pi \; z_{k}\sin \; {\delta/\lambda}} - {\epsilon_{j}z_{k}}} )} \rbrack}}} \}}}$

where δ is a radar depression angle. Given a small depression angle, inone example, point target responses of a quartet may be consideredcollocated and the quartets of correlated responses may be simplified to

$I_{j} = {\sum\limits_{k}^{\;}{{P( {x_{k},y_{k}} )}{\exp \lbrack {i( {{\alpha_{j}x_{k}} + {4\pi \; {y_{k}/\lambda}}} )} \rbrack}\{ {{a_{k}{\exp ( {i\; \epsilon_{j}z_{k}} )}} + {b_{k}{\exp \lbrack {i\; 4\; \pi \; z_{k}\sin \; {\delta/\lambda}} \rbrack}{\cos ( {\epsilon_{j}z_{k}} )}} + {c_{k}{\exp \lbrack {i( {{8\pi \; z_{k}\sin \; {\delta/\lambda}} - {\epsilon_{j}z_{k}}} )} \rbrack}}} \}}}$

There are six parameters (a_(k), b_(k), c_(k), x_(k), y_(k), z_(k)) tobe determined per quartet, so the interferometric processor maydetermine parameters of up to N/3 quartets per resolution cell.

In one example, the interferometric processor 450 may outputrange/cross-range and interferometric response position locations thatmay be fused into scatterer position measurements in a scattererprocessor 460, accounting for heights of some ground-bounce responsesbeing measured as zero (ground level) or the negative of the actualheight. In one example, scatterer measurements may be clustered toprovide object (e.g., obstacle) location and extent measurements.

FIG. 5 illustrates an example block diagram 500 of an automotive radarseparated into transmit antenna elements 530, receive antenna elements540, an automotive radar transceiver 550 with digitized data 560 flowingfrom the radar transceiver 550, and a radar microcontroller 560. In oneexample, radar microcontroller may include one or more of the componentsshown in FIG. 4.

FIG. 6 illustrates an example flow diagram 600 for measuring positionsand extents of obstacles on a road. In block 610, generate a transmitradar waveform. In one example, the transmit radar waveform may be acoherent pulsed radar waveform with a plurality of pulses over acoherent time duration. In one example, the step in block 610 may beperformed by a radar transceiver, for example, the radar transceiver 410shown in FIG. 4.

In block 620, receive a receive radar waveform and generate a digitizedradar data from the receive radar waveform. In one example, the receiveradar waveform is a scaled replica of the transmit radar waveform. Inone example, the receive radar waveform is a scaled replica of thetransmit radar waveform with a time delay τ (tau) and a Doppler shift ν(nu) for a scatterer. In one example, the digitized radar data includesamplitude information and phase information of the receive radarwaveform. In one example, the step in block 620 may be performed by aradar transceiver, for example, the radar transceiver 410 shown in FIG.4.

In block 630, form a flow of range/cross-range radar images from thedigitized radar data. In one example, the flow of range/cross-rangeradar images includes a plurality of resolution cells. In one example,the plurality of resolution cells includes a range resolution determinedby a signal bandwidth and a cross-range resolution determined by anangular rotation of radar line of sight. In one example, the step inblock 630 may be performed by an image processor, for example, the imageprocessor 430 shown in FIG. 4.

In block 640, generate a flow of range/Doppler detections from the flowof range/cross-range radar images. In one example, the flow ofrange/Doppler detections is used for thresholding, Constant False AlarmRate (CFAR) detection, or similar detection operation. In one example,the step in block 640 may be performed by a detection processor, forexample, the detection processor 440 shown in FIG. 4.

In block 650, create interferometric measurements to generate a flow ofresponse position locations using the flow of range/Doppler detectionsby fitting a parametric expression. In one example, the parametricexpression may incorporate relative spacing of ground-bounce and directreturns from each scatterer. In one example, the step in block 650 maybe performed by an interferometric processor, for example, theinterferometric processor 450 shown in FIG. 4.

In block 660, derive scatterer positions and obstacle position andextent measurements from the flow of response position locations. In oneexample, the scatterer positions and obstacle position and extentmeasurements may be derived by clustering of response positions,accounting for some ground-bounce response positions being measured atground level (height zero) or at the negative of the actual height. Inone example, the step in block 660 may be performed by a scattererprocessor, for example, the scatterer processor 460 shown in FIG. 4.

In one aspect, one or more of the process or flow disclosed herein maybe executed by one or more processors which may include hardware,software, firmware, etc. The one or more processors, for example, mayinclude one or more memory units to execute software or firmware neededto perform any part of the process or flow described herein. In oneexample, the memory unit may be one or more of the following: a randomaccess memory (RAM), a read only memory (ROM), a programmable ROM(PROM), an erasable PROM (EPROM), and/or an electrically erasable PROM(EEPROM), etc.

In one example, for a hardware implementation, the processing units maybe implemented within one or more application specific integratedcircuits (ASICs), digital signal processors (DSPs), digital signalprocessing devices (DSPDs), programmable logic devices (PLDs), fieldprogrammable gate arrays (FPGAs), processors, controllers,micro-controllers, microprocessors, other electronic units designed toperform the functions described therein, or a combination thereof. Withsoftware, the implementation may be through modules (e.g., procedures,functions, etc.) that performs the functions described therein. Thesoftware codes may be stored in memory units and executed by a processorunit. Additionally, the various illustrative flow diagrams, logicalblocks, modules and/or algorithm steps described herein may also becoded as computer-readable instructions carried on any computer-readablemedium known in the art or implemented in any computer program productknown in the art.

Software shall be construed broadly to mean instructions, instructionsets, code, code segments, program code, programs, subprograms, softwaremodules, applications, software applications, software packages,routines, subroutines, objects, executables, threads of execution,procedures, functions, etc., whether referred to as software, firmware,middleware, microcode, hardware description language, or otherwise.

The software may reside on a computer-readable medium. Thecomputer-readable medium may be a non-transitory computer-readablemedium. A non-transitory computer-readable medium includes, by way ofexample, a magnetic storage device (e.g., hard disk, floppy disk,magnetic strip), an optical disk (e.g., a compact disc (CD) or a digitalversatile disc (DVD)), a smart card, a flash memory device (e.g., acard, a stick, or a key drive), a random access memory (RAM), a readonly memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM),an electrically erasable PROM (EEPROM), a register, a removable disk,and any other suitable medium for storing software and/or instructionsthat may be accessed and read by a computer.

The computer-readable medium may also include, by way of example, acarrier wave, a transmission line, and any other suitable medium fortransmitting software and/or instructions that may be accessed and readby a computer. The computer-readable medium may reside in the processingsystem, external to the processing system, or distributed acrossmultiple entities including the processing system. The computer-readablemedium may be embodied in a computer program product. By way of example,a computer program product may include a computer-readable medium inpackaging materials. The computer-readable medium may include softwareor firmware for performing any of the process or flow described herein.Those skilled in the art will recognize how best to implement thedescribed functionality presented throughout this disclosure dependingon the particular application and the overall design constraints imposedon the overall system.

What is claimed is:
 1. A method for obstacle detection, the methodcomprising: creating one or more interferometric measurements togenerate a flow of response position locations using a flow ofrange/Doppler detections by fitting a parametric expression; andderiving one or more scatterer positions and obstacle position andextent measurements from the flow of response position locations.
 2. Themethod of claim 1, further comprising receiving a receive radar waveformand generating digitized radar data from the receive radar waveform. 3.The method of claim 2, wherein the receive radar waveform is a scaledreplica of a transmit radar waveform with a time delay τ (tau) and aDoppler shift ν (nu) for a scatterer.
 4. The method of claim 2, whereinthe receive radar waveform is a scaled replica of a transmit radarwaveform.
 5. The method of claim 2, further comprising forming a flow ofrange/cross-range radar images from the digitized radar data.
 6. Themethod of claim 5, wherein the flow of range/cross-range radar imagescomprises a plurality of resolution cells.
 7. The method of claim 6,wherein the plurality of resolution cells includes a range resolutiondetermined by a signal bandwidth and a cross-range resolution determinedby an angular rotation of radar line of sight.
 8. The method of claim 5,further comprising generating the flow of range/Doppler detections fromthe flow of range/cross-range radar images.
 9. The method of claim 4,further comprising generating the transmit radar waveform, wherein thetransmit radar waveform is a coherent pulsed radar waveform with aplurality of pulses over a coherent time duration.
 10. The method ofclaim 1, wherein the parametric expression includes a relative spacingof a ground-bounce and a direct return from a scatterer.
 11. The methodof claim 1, further comprising deriving the one or more scattererpositions and obstacle position and extent measurements by determining asimultaneous solution for a plurality of scatterers with a least-squaresfit using numerical optimization.
 12. The method of claim 1, furthercomprising deriving the one or more scatterer positions and obstacleposition and extent measurements by determining an iterativescatterer-by-scatterer solution based on a deconvolution algorithm. 13.The method of claim 12, wherein the deconvolution algorithm is a CLEANalgorithm.
 14. An apparatus for obstacle detection, the apparatuscomprising: an interferometric processor to create one or moreinterferometric measurements to generate a flow of response positionlocations using a flow of range/Doppler detections by fitting aparametric expression; and a scatterer processor, coupled to theinterferometric processor, to derive one or more scatterer positions andobstacle position and extent measurements from the flow of responseposition locations.
 15. The apparatus of claim 14, wherein theinterferometric processor and the scatterer processor are two separatecomponents of the apparatus.
 16. The apparatus of claim 14, furthercomprising a radar transceiver to receive a receive radar waveform andto generate a digitized radar data from the receive radar waveform. 17.The apparatus of claim 16, wherein the receive radar waveform is ascaled replica of a transmit radar waveform with a time delay τ (tau)and a Doppler shift ν (nu) for a scatterer.
 18. The apparatus of claim17, wherein the transmit radar waveform is a coherent pulsed radarwaveform with a plurality of pulses over a coherent time duration. 19.The apparatus of claim 16, further comprising an image processor,coupled to the radar transceiver, to form a flow of range/cross-rangeradar images from the digitized radar data.
 20. The apparatus of claim19, further comprising a detection processor, coupled to the imageprocessor, to generate the flow of range/Doppler detections from theflow of range/cross-range radar images.
 21. The apparatus of claim 14,wherein the scatterer processor derives the one or more scattererpositions and obstacle position and extent measurements by determining asimultaneous solution for a plurality of scatterers with a least-squaresfit using numerical optimization.
 22. The apparatus of claim 14, whereinthe scatterer processor derives the one or more scatterer positions andobstacle position and extent measurements by determining an iterativescatterer-by-scatterer solution based on a deconvolution algorithm.